EMG Feature Extraction Toolbox

Versione 1.4 (17,4 KB) da Jingwei Too

This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.

https://jingweitoo.wordpress.com/

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4.4

(8)

4K download

Aggiornato 11 dic 2020

Visualizza la licenza su GitHub

Jx-EMGT : Electromyography (EMG) Feature Extraction Toolbox

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* This toolbox offers 40 types of EMG features

* The < A_Main.m file > demos how the feature extraction methods can be applied using generated sample signal.

* The detailed of this Jx-EMGT toolbox can be found at https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox

Cita come

Too, Jingwei, et al. “Classification of Hand Movements Based on Discrete Wavelet Transform and Enhanced Feature Extraction.” International Journal of Advanced Computer Science and Applications, vol. 10, no. 6, The Science and Information Organization, 2019, doi:10.14569/ijacsa.2019.0100612.

Visualizza più stili

Too, Jingwei, et al. “EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization.” Computation, vol. 7, no. 1, MDPI AG, Feb. 2019, p. 12, doi:10.3390/computation7010012.

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Compatibilità della release di MATLAB

Creato con R2018a

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Categorie

Signal Processing > Wavelet Toolbox > Discrete Multiresolution Analysis >

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Ispirato: Identify Arm Motions Using EMG Signals and Deep Learning.

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Versione	Pubblicato	Note della release
1.4	11 dic 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/EMG-Feature-Extraction-Toolbox/releases/tag/1.4	Scarica

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.

MLA	Too, Jingwei, et al. “Classification of Hand Movements Based on Discrete Wavelet Transform and Enhanced Feature Extraction.” International Journal of Advanced Computer Science and Applications, vol. 10, no. 6, The Science and Information Organization, 2019, doi:10.14569/ijacsa.2019.0100612.
APA	Too, J., Rahim, A., & Mohd, N. (2019). Classification of Hand Movements based on Discrete Wavelet Transform and Enhanced Feature Extraction. International Journal of Advanced Computer Science and Applications, 10(6). The Science and Information Organization. Retrieved from https://doi.org/10.14569%2Fijacsa.2019.0100612
BibTeX	@article{Too_2019, doi = {10.14569/ijacsa.2019.0100612}, url = {https://doi.org/10.14569%2Fijacsa.2019.0100612}, year = 2019, publisher = {The Science and Information Organization}, volume = {10}, number = {6}, author = {Jingwei Too and Abdul Rahim and Norhashimah Mohd}, title = {Classification of Hand Movements based on Discrete Wavelet Transform and Enhanced Feature Extraction}, journal = {International Journal of Advanced Computer Science and Applications} }

MLA	Too, Jingwei, et al. “EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization.” Computation, vol. 7, no. 1, MDPI AG, Feb. 2019, p. 12, doi:10.3390/computation7010012.
APA	Too, J., Abdullah, A., Saad, N. M., & Tee, W. (2019). EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization. Computation, 7(1), 12. MDPI AG. Retrieved from https://doi.org/10.3390%2Fcomputation7010012
BibTeX	@article{Too_2019, doi = {10.3390/computation7010012}, url = {https://doi.org/10.3390%2Fcomputation7010012}, year = 2019, month = {feb}, publisher = {{MDPI} {AG}}, volume = {7}, number = {1}, pages = {12}, author = {Jingwei Too and Abdul Abdullah and Norhashimah Mohd Saad and Weihown Tee}, title = {{EMG} Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization}, journal = {Computation} }